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Mission_to_Mars_Challange.py
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Mission_to_Mars_Challange.py
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#!/usr/bin/env python
# coding: utf-8
# In[1]:
# Import Splinter and BeautifulSoup
from splinter import Browser
from bs4 import BeautifulSoup as soup
from webdriver_manager.chrome import ChromeDriverManager
import pandas as pd
# In[2]:
executable_path = {'executable_path':ChromeDriverManager().install()}
browser = Browser('chrome', **executable_path, headless=False)
# In[3]:
# Visit the mars nasa news site
url = 'https://redplanetscience.com'
browser.visit(url)
# Optional delay for loading the page
browser.is_element_present_by_css('div.list_text', wait_time=1)
# In[4]:
html = browser.html
news_soup = soup(html, 'html.parser')
slide_elem = news_soup.select_one('div.list_text')
# In[5]:
slide_elem.find('div',class_='content_title')
# In[6]:
# Use the parent element to find the first `a` tag and save it as `news_title`
news_title = slide_elem.find('div',class_='content_title').get_text()
news_title
# In[7]:
# Use the parent element to find the paragraph text
news_p = slide_elem.find('div',class_='article_teaser_body').get_text()
news_p
# #### Scraping Image
# ### Features Images
# In[8]:
# Visit URL
url = 'https://spaceimages-mars.com'
browser.visit(url)
# In[9]:
# Find and click the full image button
full_image_elem = browser.find_by_tag('button')[1]
full_image_elem.click()
# In[10]:
# Parse the resulting html with soup
html = browser.html
img_soup = soup(html, 'html.parser')
# In[11]:
# Find the relative image url
img_url_rel = img_soup.find('img', class_='fancybox-image').get('src')
img_url_rel
# In[12]:
# Use the base URL to create an absolute URL
img_url = f'https://spaceimages-mars.com/{img_url_rel}'
img_url
# ### Scrape Mars Data: Mars Facts
# In[13]:
# Visit URL
url = 'https://galaxyfacts-mars.com/'
browser.visit(url)
# In[14]:
df = pd.read_html('https://galaxyfacts-mars.com')[0]
df.columns=['description', 'Mars', 'Earth']
df.set_index('description', inplace=True)
df
# In[15]:
# Turn the DataFrame into HTML-ready code
df.to_html()
# In[16]:
# Add the code to end the automated browsing session
browser.quit()
# In[65]:
# Import Splinter, BeautifulSoup, and Pandas
from splinter import Browser
from bs4 import BeautifulSoup as soup
import pandas as pd
from webdriver_manager.chrome import ChromeDriverManager
# In[66]:
# Set the executable path and initialize Splinter
executable_path = {'executable_path': ChromeDriverManager().install()}
browser = Browser('chrome', **executable_path, headless=False)
# ### Visit the NASA Mars News Site
# In[19]:
# Visit the mars nasa news site
url = 'https://redplanetscience.com/'
browser.visit(url)
# Optional delay for loading the page
browser.is_element_present_by_css('div.list_text', wait_time=1)
# In[20]:
# Convert the browser html to a soup object and then quit the browser
html = browser.html
news_soup = soup(html, 'html.parser')
slide_elem = news_soup.select_one('div.list_text')
# In[21]:
slide_elem.find('div', class_='content_title')
# In[22]:
# Use the parent element to find the first a tag and save it as `news_title`
news_title = slide_elem.find('div', class_='content_title').get_text()
news_title
# In[23]:
# Use the parent element to find the paragraph text
news_p = slide_elem.find('div', class_='article_teaser_body').get_text()
news_p
# ### JPL Space Images Featured Image
# In[24]:
# Visit URL
url = 'https://spaceimages-mars.com'
browser.visit(url)
# In[25]:
# Find and click the full image button
full_image_elem = browser.find_by_tag('button')[1]
full_image_elem.click()
# In[26]:
# Parse the resulting html with soup
html = browser.html
img_soup = soup(html, 'html.parser')
img_soup
# In[27]:
# find the relative image url
img_url_rel = img_soup.find('img', class_='fancybox-image').get('src')
img_url_rel
# In[28]:
# Use the base url to create an absolute url
img_url = f'https://spaceimages-mars.com/{img_url_rel}'
img_url
# ### Mars Facts
# In[29]:
df = pd.read_html('https://galaxyfacts-mars.com')[0]
df.head()
# In[30]:
df.columns=['Description', 'Mars', 'Earth']
df.set_index('Description', inplace=True)
df
# In[31]:
df.to_html()
# # D1: Scrape High-Resolution Mars’ Hemisphere Images and Titles
# ### Hemispheres
# In[67]:
# 1. Use browser to visit the URL
url = "https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars"
browser.visit(url)
# In[68]:
# 2. Create a list to hold the images and titles.
hemisphere_image_urls = []
# 3. Write code to retrieve the image urls and titles for each hemisphere.
# Given there are 4 search results in the page, identify the variable representing the number of search results.
results = browser.find_by_css("h3")
# Create the loop through the search results.
for item in range(len(results)):
# Create an empty dictionary to hold image url and title data
hemisphere = {}
# Find element on each loop and click
browser.find_by_css("h3")[item].click()
# Find Image tag and Extract
sample_element = browser.find_link_by_text("Sample").first
hemisphere['img_url'] = sample_element['href']
# Retrieve Hemisphere title
hemisphere['title'] = browser.find_by_css("h2.title").text
# Append Hemisphere data to List
hemisphere_image_urls.append(hemisphere)
# Navigate the page back
browser.back
# In[69]:
# 4. Print the list that holds the dictionary of each image url and title.
hemisphere_image_urls
# In[35]:
# 5. Quit the browser
browser.quit()
# In[ ]: